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Particle Cloud Simulation

This notebook uses the same setup as detailed_look.jl / example2(). For additional documentation e.g. see : 1, 2, 3, 4

1. Import Software

using IndividualDisplacements, OrdinaryDiffEq, Statistics
p=dirname(pathof(IndividualDisplacements))
include(joinpath(p,"../examples/recipes_plots.jl"))
include(joinpath(p,"../examples/example123.jl"))
Main.ex-particle_cloud.OCCA_setup

2. Setup Problem

uvetc=example2_setup()

#ii1=1:10:80; ii2=1:10:42; #->sol is (2, 40, 40065)
#ii1=30:37; ii2=16:20; #->sol is (2, 40, 9674)
#ii1=10:17; ii2=16:20; #->sol is (2, 40, 51709)
ii1=5:5:40; ii2=5:5:25; #->sol is (2, 40, 51709)

n1=length(ii1); n2=length(ii2);
u0=Array{Float64,2}(undef,(2,n1*n2))
for i1 in eachindex(ii1); for i2 in eachindex(ii2);
        i=i1+(i2-1)*n1
        u0[1,i]=ii1[i1]-0.5
        u0[2,i]=ii2[i2]-0.5
end; end;

3. Compute Trajectories

  • Define an ODE problem.
  • Solve the ODE problem to compute trajectories.
𝑇 = (0.0,2998.0*3600.0)
prob = ODEProblem(⬡,u0,𝑇,uvetc)

sol = solve(prob,Tsit5(),reltol=1e-6,abstol=1e-6)
size(sol)
(2, 40, 7157)

4. Display results

ID=collect(1:size(sol,2))*ones(1,size(sol,3))
lon=5000* mod.(sol[1,:,:],80); lat=5000* mod.(sol[2,:,:],42)
df = DataFrame(ID=Int.(ID[:]), lon=lon[:], lat=lat[:])
plt=PlotBasic(df,size(sol,2),100000.0)
0 1×10 5 2×10 5 3×10 5 4×10 5 0 5.0×10 4 1.0×10 5 1.5×10 5 2.0×10 5

Compare with trajectory output from MITgcm

df_from_mitgcm=read_flt(joinpath(p,"../examples/flt_example/"),Float32)
plt=PlotBasic(df_from_mitgcm,40,100000.0)
0 1×10 5 2×10 5 3×10 5 4×10 5 0 5.0×10 4 1.0×10 5 1.5×10 5 2.0×10 5

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